The performance (i.e. efficacy) of targeted content delivery to a user in an on-line web based environment is typically measured by its relevancy to the audience. Content in this context can, for example, be an advertisement or a piece of media such as a video, a music file, etc., delivered to a computing device for presentation to a user or subscriber. The performance can typically be optimized by having an increasing amount of information related to an audience's historical consumption of content (e.g. websites visits, searches), near-term web activities (e.g. search, eCommerce transactions, etc.), as well as by observing and comparing to other similar audiences' behaviors.
In the existing art, network application elements (i.e. systems that deliver applications and/or services that are located within, or interwork with, a communication provider's network) and targeted content delivery systems are typical implemented as standalone solutions thus missing the opportunities to leverage the strengths offered by each solution and the synergy of coupling these solutions to increase both targeting relevancy performance and financial uplift performance.
What is needed is a solution that addresses the targeting performance optimization problem by leveraging the rich sources of data that reside within the network application elements. Accordingly, a method and system that enable targeted content delivery based on network application data generated by a subscriber remain highly desirable.